Senior Data Scientist

UptimeAI provides AI reasoning agents that help industrial operations teams make goal-oriented, real-time decisions.

Industrial facilities are rich in data but constrained by the expertise required to maintain and interpret it. As experienced engineers retire and operational complexity grows, organizations struggle to scale the expert judgment needed to maintain reliability, safety, and performance.

UptimeAI addresses this challenge by embedding engineering reasoning directly into AI agents that continuously analyze operational data, diagnose issues, and guide teams toward the best actions. The result is faster decisions, reduced downtime, improved efficiency, and stronger operational performance.

We are looking for individuals who sit at the intersection of Data Science and Physical Sciences. You understand that industrial data isn't just rows in a database—it represents thermo dynamics, fluid dynamics, and mechanical stress. The candidate should be capable of translating business problems into scalable AI solutions, leveraging creative thinking and first-principles problem solving.

This role requires someone who can:

• Build and deploy production-grade AI systems, not just prototypes

• Design agentic workflows that can reason, adapt and take actions in dynamic environments

• Work with noisy, incomplete, and real-time industrial data to derive meaningful insights

• Collaborate closely with domain experts (e.g., operations, reliability, or plant engineers) to create context-aware AI solutions

• Demonstrate innovative thinking in solving ambiguous problems where standard approaches may not apply

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  Be a part of the design, development, and deployment of advanced AI/ML models for predictive maintenance, process optimization, and industrial performance intelligence

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  Collaborate closely with Product, Engineering, and Customer Success teams to translate business problems from industrial domains into data science solutions.

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  Guide the team in handling complex, high-dimensional, and time-series sensor data from IoT, SCADA, and DCS systems.

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  Drive model interpretability, scalability, and accuracy, ensuring robust performance in real-world production environments.

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• Bachelor’s or higher in Chemical Engineering, Mechanical Engineering, Aerospace, or Applied Physics with a heavy emphasis on computational modeling. (Candidates with CS degrees are welcome if they have significant experience in heavy industry).

• 5+ years of hands-on experience developing and deploying ML models specifically within Manufacturing, Energy, Oil & Gas, or Power sectors.

• Strong background in handling time-series and sensor data from industrial or IoT systems.

• Hands-on experience with Python, TensorFlow/PyTorch, Scikit-learn, SQL, and cloud ML platforms (AWS, Azure, GCP).

• Excellent problem-solving and communication skills with the ability to influence senior stakeholders.

• Demonstrated ability to lead and mentor teams while being a hands-on contributor

• Ability to work independently, with strong problem-solving and decision-making abilities

• Impact Industry-Wide Change: Contribute to transformative solutions that significantly improve operational efficiency and reliability for global clients.

• Collaborative and Growth-Oriented Environment: Join a talented, passionate team that values innovation, continuous learning, and professional growth.

• Opportunities for Leadership and Innovation: Lead pioneering projects, influence product development, and shape the future of industrial AI solutions.